Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study

Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Biotechnology and Bachelor of Science in Microbiology, 2023.

Xehetasun bibliografikoak
Egile nagusia:	Faisal, Shah
Beste egile batzuk:	Haque, Munima
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Cervical cancer Comparative analysis Predictive modeling Machine learning Healthcare infrastructure Cervix uteri > Cancer > Diagnosis. Machine learning > Computer programs
Sarrera elektronikoa:	http://hdl.handle.net/10361/22686

Antzeko izenburuak

Early detection of cervical cancer using deep neural networks
nork: Akhund, Atoshi, et al.
Argitaratua: (2023)

Decoding the functional roles of intronic microRNA miR-2355 and its host gene KLF7 in immunobiology of cervical cancer
nork: Samia, Nure Sharaf Nower
Argitaratua: (2021)

Machine learning as an indicator for breast cancer prediction
nork: Shadman, Tahsin Mohammed, et al.
Argitaratua: (2019)

Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN
nork: Bhuiyan, Mazedul Haque, et al.
Argitaratua: (2021)

Breast cancer prediction using different machine learning models
nork: Khandker Al- Muhaimin, et al.
Argitaratua: (2020)

Diagnosis of cervical cancer using effective hybrid model in Bangladesh
nork: Saad-Ul-Kabir, Syed, et al.
Argitaratua: (2021)

A comparative analysis of deep learning and hybrid models to diagnose multi-class skin cancer
nork: Nawrin, Ishrat Nur, et al.
Argitaratua: (2023)

Lung cancer detection and classification using machine learning
nork: Arefin, Mahbubul, et al.
Argitaratua: (2023)

A review on the socio-demographic and cultural factors associated with the delayed diagnosis of cervical cancer and possible interventions in screening attitude: From South Asian perspective
nork: Tarannum, Nafisa, et al.
Argitaratua: (2023)

Early detection of breast cancer using machine learning
nork: Fuad, Wasi Mohammad
Argitaratua: (2019)

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
nork: Sakib, Hasibul, et al.
Argitaratua: (2024)

Review on cervical cancer: effective vaccination project
nork: Humayra, Ayonti
Argitaratua: (2024)

Awareness of cervical cancer vaccination among educated females: a Bangladeshi perspective
nork: Taniya, Sumaiya Akter
Argitaratua: (2023)

Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
nork: Chowdhury, Himadri, et al.
Argitaratua: (2019)

Survey on patients undergoing treatments for cervical, endometrial and ovarian cancer
nork: Nawar, Anika
Argitaratua: (2019)

Detection of skin cancer using Convolutional neural network
nork: Ahsan, Abu Sa-adat Mohamed Moon-Im Al, et al.
Argitaratua: (2020)

Predicting climate induced floods using machine learning
nork: Saleh, Chowdhury Nafis, et al.
Argitaratua: (2022)

Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
nork: Hasan, Raad, et al.
Argitaratua: (2021)

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
nork: Oishi, Fayza Rezwana, et al.
Argitaratua: (2020)

Point-of care diagnostic devices in cancer detection
nork: Yasmin, Rizwana
Argitaratua: (2022)

Machine learning In breast cancer prognosis and prediction
nork: Chowdhury, Shah Abul Hasnat, et al.
Argitaratua: (2023)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
nork: Islam, Zahedul, et al.
Argitaratua: (2023)

An efficient deep learning approach to detect skin Cancer
nork: Islam, Ashfaqul, et al.
Argitaratua: (2022)

Developing a machine learning based prognostic model and a supporting web-based application for predicting the possibility of early diabetes and diabetic kidney disease
nork: Amin, M.M. Shahriar, et al.
Argitaratua: (2021)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
nork: Toufique, S.M, et al.
Argitaratua: (2024)

Recent advancement on breast cancer detection and treatment
nork: Rahman, Sanjida
Argitaratua: (2023)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
nork: Alhossen, Md., et al.
Argitaratua: (2021)

Skin cancer classification for seven types of skin lesions
nork: Rahman, Md. Tawsifur, et al.
Argitaratua: (2024)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
nork: Sakir, Adnan, et al.
Argitaratua: (2023)

A counseling system to predict the study path for freshmen
nork: Usha, Rowshni Tasneem, et al.
Argitaratua: (2019)

Yield prediction for precision agriculture using extreme gradient boosting and support vector regression
nork: Ahmed, Md. Sabbir, et al.
Argitaratua: (2021)

Machine learning for stress prediction
nork: Salehin, Sherajus, et al.
Argitaratua: (2023)

A comparative study of lung cancer prediction using deep learning
nork: Mugdho, Aka Mohammad, et al.
Argitaratua: (2023)

Heart disease prediction using machine learning algorithms
nork: Ali, Musfiq, et al.
Argitaratua: (2019)

Statistics and informatics in molecular cancer research

Prostate cancer detection using deep learning neural network with transfer learning approach
nork: Badhon, Ariful Islam Mahmud, et al.
Argitaratua: (2022)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
nork: Maliha, Miftahul Zannat, et al.
Argitaratua: (2023)

Detecting Adverse Drug Reaction (ADR) with data mining and predicting its intensity with machine learning
nork: Hussain, Nadib, et al.
Argitaratua: (2018)

Prediction of anxiety and depression among the transgender in Bangladesh
nork: Easha, Ishrat Jahan, et al.
Argitaratua: (2023)

Investigation assistant with suspect anticipating intelligence
nork: Abdullah, Saqueeb, et al.
Argitaratua: (2019)